Flying Laser Range Sensor for Large-Scale Site-Modeling and Its Applications in Bayon Digital Archival Project

  • Authors:

  • A. Banno;T. Masuda;T. Oishi;K. Ikeuchi

  • Affiliations:

  • Graduate School of Information Science and Technology, University of Tokyo, Tokyo, Japan 153-8505;Graduate School of Information Science and Technology, University of Tokyo, Tokyo, Japan 153-8505;Graduate School of Interdisciplinary Information Studies, University of Tokyo, Tokyo, Japan 153-8505;Graduate School of Interdisciplinary Information Studies, University of Tokyo, Tokyo, Japan 153-8505

  • Venue:
  • International Journal of Computer Vision
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

Abstract

We have been conducting a project to digitize the Bayon temple, located at the center of Angkor-Thom in the kingdom of Cambodia. This is a huge structure, more than 150 meters long on all sides and up to 45 meters high. Digitizing such a large-scale object in fine detail requires developing new types of sensors for obtaining data of various kinds related to irregular positions such as the very high parts of the structure occluded from the ground. In this article, we present a sensing system with a moving platform, referred to as the Flying Laser Range Sensor (FLRS), for obtaining data related to these high structures from above them. The FLRS, suspended beneath a balloon, can be maneuvered freely in the sky and can measure structures invisible from the ground. The obtained data, however, has some distortion due to the movement of the sensor during the scanning process. In order to remedy this issue, we have developed several new rectification algorithms for the FLRS. One method is an extension of the 3D alignment algorithm to estimate not only rotation and translation but also motion parameters. This algorithm compares range data of overlapping regions from ground-based sensors and our FLRS. Another method accurately estimates the FLRS's position by combining range data and image sequences from a video camera mounted on the FLRS. We evaluate these algorithms using a IS-based method and verify that both methods achieve much higher accuracy than previous methods.